{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filtered data points:\n",
      "[[-0.28836024  0.2374001 ]\n",
      " [ 0.81296057 -0.70939056]\n",
      " [-0.09659169  0.04262385]\n",
      " ...\n",
      " [ 0.52965735  0.95306245]\n",
      " [ 0.27305822  0.57972409]\n",
      " [ 1.09868914 -0.80030618]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.stats import gaussian_kde\n",
    "\n",
    "# 准备数据\n",
    "data = np.random.multivariate_normal(mean=[0, 0], cov=[[1, 0.5], [0.5, 1]], size=1000)  # 示例数据，可以替换为你的实际数据\n",
    "\n",
    "# 初始化KDE模型\n",
    "kde = gaussian_kde(data.T)  # 注意要将数据转置\n",
    "\n",
    "# 计算概率密度估计值\n",
    "density = kde.evaluate(data.T)\n",
    "\n",
    "# 指定前百分数\n",
    "percentile = 0.99  # 替换为你要计算的百分数值\n",
    "\n",
    "# 计算概率密度的阈值\n",
    "threshold = np.quantile(density, 1 - percentile)\n",
    "\n",
    "# 筛选出不是离群点的数据\n",
    "filtered_data = data[density >= threshold]\n",
    "\n",
    "# 打印筛选后的数据\n",
    "print(f\"Filtered data points:\\n{filtered_data}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1000, 2), (990, 2), (1000,))"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape,filtered_data.shape,density.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x18d8155fee0>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(data[:,0],data[:,1],color = \"b\")\n",
    "plt.scatter(filtered_data[:,0],filtered_data[:,1],color = \"r\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
